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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.9836033950617284

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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.865940940940941

<Figure size 432x288 with 0 Axes>

<Figure size 432x288 with 0 Axes>

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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.9033794210877544

<Figure size 432x288 with 0 Axes>

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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.9038267434100767

<Figure size 432x288 with 0 Axes>

<Figure size 432x288 with 0 Axes>

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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.9001803887220554

<Figure size 432x288 with 0 Axes>

<Figure size 432x288 with 0 Axes>

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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.8811373873873873

<Figure size 432x288 with 0 Axes>

<Figure size 432x288 with 0 Axes>

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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels

0 0 0 0 ... 0 0 0

1 0 0 0 ... 0 0 0

2 0 0 0 ... 0 0 0

3 0 0 0 ... 0 0 0

4 0 0 0 ... 0 0 0

[5 rows x 44 columns]

Random Forest Accuracy = 0.895925091758425

<Figure size 432x288 with 0 Axes>

<Figure size 432x288 with 0 Axes>

Traceback (most recent call last):

File C:\Dev\Python\biomedical_term\Lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec

exec(code, globals, locals)

File c:\dev\python\biomedical_term\homew.py:468

plot(segmented_selected_perm,f"{ml_algo[k+1]} selected 'Permutation' estimated result")

File c:\dev\python\biomedical_term\homew.py:39 in plot

plt.show()

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\pyplot.py:446 in show

return _get_backend_mod().show(*args, **kwargs)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib_inline\backend_inline.py:90 in show

display(

File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\display_functions.py:298 in display

format_dict, md_dict = format(obj, include=include, exclude=exclude)

File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\formatters.py:179 in format

data = formatter(obj)

File C:\Dev\Python\biomedical_term\Lib\site-packages\decorator.py:232 in fun

return caller(func, *(extras + args), **kw)

File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\formatters.py:223 in catch_format_error

r = method(self, *args, **kwargs)

File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\formatters.py:340 in __call__

return printer(obj)

File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\pylabtools.py:152 in print_figure

fig.canvas.print_figure(bytes_io, **kw)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backend_bases.py:2366 in print_figure

result = print_method(

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backend_bases.py:2232 in <lambda>

print_method = functools.wraps(meth)(lambda *args, **kwargs: meth(

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backends\backend_agg.py:509 in print_png

self._print_pil(filename_or_obj, "png", pil_kwargs, metadata)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backends\backend_agg.py:457 in _print_pil

FigureCanvasAgg.draw(self)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backends\backend_agg.py:400 in draw

self.figure.draw(self.renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:95 in draw_wrapper

result = draw(artist, renderer, *args, **kwargs)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper

return draw(artist, renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\figure.py:3140 in draw

mimage._draw_list_compositing_images(

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\image.py:131 in _draw_list_compositing_images

a.draw(renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper

return draw(artist, renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\axes\_base.py:3064 in draw

mimage._draw_list_compositing_images(

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\image.py:131 in _draw_list_compositing_images

a.draw(renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper

return draw(artist, renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\axis.py:1380 in draw

tick.draw(renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper

return draw(artist, renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\axis.py:301 in draw

artist.draw(renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper

return draw(artist, renderer)

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\lines.py:856 in draw

marker_trans = marker.get_transform()

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\markers.py:384 in get_transform

return self._transform.frozen()

File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\transforms.py:1829 in frozen

return Affine2D(self.get_matrix().copy())

KeyboardInterrupt

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